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Testing The Hypothesis Of Martingale On Intraday Data: The Case Of Bet Index

Author

Listed:
  • Alexandru Todea

    (“Babeş-Bolyai” University, Cluj-Napoca)

  • Anita Pleşoianu

    (“Babeş-Bolyai” University, Cluj-Napoca)

Abstract

The hypothesis of martingale on Romanian capital market is tested based on the intraday data of the BET index for the time period November 2, 2009 through April 30, 2010. Investigation of this hypothesis is realized through two recent test, the Automatic Variance Ratio test of Kim (2009) and the Generalized Spectral test of Escanciano and Velasco (2006). The first has the best performance in the presence of linear dependencies, while the high performance of the second is in the presence of nonlinear dependencies. The robustness of the two tests in the presence of heteroskedasticity is given by using a wild boostrap methodology. The empirical results reject the hypothesis of martingale especially due to the presence of nonlinear dependencies in the intraday data, indicating the existence of a high potential of predictability.

Suggested Citation

  • Alexandru Todea & Anita Pleşoianu, 2011. "Testing The Hypothesis Of Martingale On Intraday Data: The Case Of Bet Index," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 5(5(558)(su), pages 344-351, July.
    • Handle: RePEc:agr:journl:v:5(558)(supplement):y:2011:i:5(558)(supplement):p:344-351
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    Citations

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    Cited by:

    1. Dan Gabriel ANGHEL, 2017. "Intraday Market Efficiency for a Typical Central and Eastern European Stock Market: The Case of Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 88-109, September.
    2. Dan Gabriel ANGHEL & Elena Valentina ŢILICĂ & Victor DRAGOTĂ, 2020. "Intraday Patterns in Returns on the Romanian and Bulgarian Stock Markets," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 92-114, July.
    3. Victor Dragota & Dragos Stefan Oprea, 2014. "Informational Efficiency Tests on the Romanian Stock Market: A Review of the Literature," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 6(1), pages 015-028, June.
    4. Eva DEZSI & Ioan Alin NISTOR, 2016. "Can Deep Machine Learning Outsmart The Market? A Comparison Between Econometric Modelling And Long- Short Term Memory," Romanian Economic Business Review, Romanian-American University, vol. 11(4.1), pages 54-73, december.

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